The massive benefit potential of Industrial Internet of Things (IIoT), and predictive analytics specifically, make them a popular topic amongst industrial organizations these days. And rightfully so. Just the prospect of avoiding unplanned downtime alone, through predictive analytics, could be worth millions. But this growing enthusiasm often exceeds an understanding of the underlying technology – in this case, machine learning. This is problematic because, due to the unique nature of each business, such comprehension is key to obtaining the necessary insights from machine learning that will help maximize ROI.
I recently contributed an article discussing the importance of gaining a fundamental grasp of machine learning to building a successful IIoT initiative. One of the themes that really stood out to me was that machine learning isn’t magic. Now, it’s not that any managers think it’s some fantasy cure-all. But the fact that it’s not some widget you plug in, turn on, then just sit back and reap rewards is increasingly obvious the more you learn about it. Likewise, all the important elements across a business that must come together to achieve a successful result become progressively clearer – and as such, easier to identify and coordinate.
That said, this are still a lot more pieces to the ROI puzzle. For a full overview of the keys to maximizing machine learning’s potential in the enterprise, check out the full article here.